filepath = "/home/CAMPUS/bawa2018/Climate_Change_Narratives/Data/FA20/Williams_SaltLakeCityUT_data.csv"
climate_data = read.csv(filepath)
strDates <- as.character(climate_data$DATE)
climate_data$NewDate <- as.Date(strDates, "%Y-%m-%d")
plot(TMAX~NewDate, climate_data, pch = 16, cex=.2, col = "blue")
TMAX.lm = lm(TMAX ~ NewDate, data = climate_data)
coef(TMAX.lm)
## (Intercept) NewDate
## 1.768352e+01 4.390910e-05
abline(coef(TMAX.lm),col ="orange", lwd = 3)
climate_data$Month = format(as.Date(climate_data$NewDate), format = "%m")
climate_data$Year = format(climate_data$NewDate, format="%Y")
MonthlyTMAXMean = aggregate(TMAX ~ Month + Year, climate_data, mean)
MonthlyTMAXMean$YEAR = as.numeric(MonthlyTMAXMean$Year)
MonthlyTMAXMean$MONTH = as.numeric(MonthlyTMAXMean$Month)
plot(MonthlyTMAXMean$TMAX, ty='l')
#plot(MonthlyTMAXMean£TMAX[MonthlyTMAXMean£Month=="05"], ty='l')
plot(TMAX~YEAR, data=MonthlyTMAXMean[MonthlyTMAXMean$Month=="05",],ty='l', xlim=c(1950, 2020))
May.lm <- lm(TMAX~YEAR, data=MonthlyTMAXMean[MonthlyTMAXMean$Month=="05",])
summary(May.lm)
##
## Call:
## lm(formula = TMAX ~ YEAR, data = MonthlyTMAXMean[MonthlyTMAXMean$Month ==
## "05", ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.8792 -1.5588 0.3994 1.6796 4.7565
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 18.275162 23.794808 0.768 0.445
## YEAR 0.002012 0.011993 0.168 0.867
##
## Residual standard error: 2.159 on 71 degrees of freedom
## Multiple R-squared: 0.0003962, Adjusted R-squared: -0.01368
## F-statistic: 0.02814 on 1 and 71 DF, p-value: 0.8672
abline(coef(May.lm), col="red")
MonthlyTMINMean = aggregate(TMIN ~ Month + Year, climate_data, mean)
MonthlyTMINMean$YEAR = as.numeric(MonthlyTMINMean$Year)
# Fixing the Format of Month and Year as numeric
MonthlyTMINMean$YEAR = as.numeric(MonthlyTMINMean$Year)
MonthlyTMINMean$MONTH = as.numeric(MonthlyTMINMean$Month)
head(MonthlyTMINMean)
## Month Year TMIN YEAR MONTH
## 1 01 1948 -6.183871 1948 1
## 2 02 1948 -4.727586 1948 2
## 3 03 1948 -3.093548 1948 3
## 4 04 1948 3.580000 1948 4
## 5 05 1948 6.990323 1948 5
## 6 06 1948 12.203333 1948 6
# First I create a vector of months
Months = c("January", "February", "March", "April",
"May", "June", "July", "August", "September", "October",
"November", "December")
# Create a panel so I can see all the figures at
# once.
par(mfrow = c(4, 3), mar = c(5, 4, 3, 2) + 0.1)
TMAXresult <-NA; TMINresult <- NA
for (i in 1:12) {
# plot(MonthlyTMAXMean£TMAX[MonthlyTMAXMean£Month==i],
# ty='l')
plot(TMAX ~ YEAR, data = MonthlyTMAXMean[MonthlyTMAXMean$MONTH == i, ], ty = "l", las = 1, xlim = c(1940, 2020), main = Months[i])
Month.lm <- lm(TMAX ~ YEAR, data = MonthlyTMAXMean[MonthlyTMAXMean$MONTH == i, ])
summary(Month.lm)
abline(coef(Month.lm), col = "red")
TMAXresult <- rbind(TMAXresult, cbind(Months[i],
round(coef(Month.lm)[2], 4), round(summary(Month.lm)$coefficients[2, 4], 4), round(summary(Month.lm)$r.squared,3)))
}
#par(mfrow=c(4,3),mar=c(5,4,1,1))
for (i in 1:12) {
MonthMin_lm <- lm(TMIN ~ YEAR, data=MonthlyTMINMean[MonthlyTMINMean$MONTH == i, ])
TMINresult <- rbind(TMINresult, cbind(Months[i],round(coef(MonthMin_lm)[2], 4), round(summary(MonthMin_lm)$coefficients[2,4], 4), round(summary(MonthMin_lm)$r.squared, 3)))
summary(MonthMin_lm)
plot(MonthlyTMINMean$TMIN, ty='l', ylab='Monthly avg min temp', xlab='Years',main=Months[i]
)
abline(coef(MonthMin_lm),col='blue')
}
library(htmlTable)
Results <- data.frame(Month = TMINresult[c(2:13),1],
TMINSlope = TMINresult[c(2:13),2],
TMIN_P = as.numeric(TMINresult[c(2:13),3]),
TMINRsq = TMINresult[c(2:13),4],
TMAXSlope = TMAXresult[c(2:13),2],
TMAX_P = as.numeric(TMAXresult[c(2:13),3]),
TMAXRsq = TMAXresult[c(2:13),4])
Results$starTMIN = "NS"
Results$starTMIN[Results$TMIN_P <= .05] = "*"
Results$starTMIN[Results$TMIN_P < 0.01] = "**"
Results$starTMIN[Results$TMIN_P < 0.001] = "***"
Results$starTMAX = "NS"
Results$starTMAX[Results$TMAX_P < 0.05] = "*"
Results$starTMAX[Results$TMAX_P < 0.01] = "**"
Results$starTMAX[Results$TMAX_P < 0.001] = "***"
Results$TMINslope=paste(Results$TMINSlope, Results$starTMIN)
Results$TMAXslope=paste(Results$TMAXSlope, Results$starTMAX)
colnames(Results) <- c("Month", "2", "3", "R^2", "5", "6",
"R^2", "8", "9", "Slope TMIN", "Slope TMAX")
htmlTable(Results[,c(1, 10, 4, 11, 7)])
|
|
Month
|
Slope TMIN
|
R^2
|
Slope TMAX
|
R^2.1
|
|
1
|
January
|
0.0454 *
|
0.081
|
0.0148 NS
|
0.011
|
|
2
|
February
|
0.039 **
|
0.097
|
0.0168 NS
|
0.016
|
|
3
|
March
|
0.0661 ***
|
0.434
|
0.0535 ***
|
0.236
|
|
4
|
April
|
0.0381 ***
|
0.245
|
0.0069 NS
|
0.005
|
|
5
|
May
|
0.0435 ***
|
0.29
|
0.002 NS
|
0
|
|
6
|
June
|
0.0604 ***
|
0.434
|
0.0247 *
|
0.054
|
|
7
|
July
|
0.0688 ***
|
0.588
|
0.019 *
|
0.07
|
|
8
|
August
|
0.0624 ***
|
0.454
|
0.0176 *
|
0.076
|
|
9
|
September
|
0.0605 ***
|
0.429
|
0.0118 NS
|
0.015
|
|
10
|
October
|
0.0352 ***
|
0.198
|
-0.0132 NS
|
0.017
|
|
11
|
November
|
0.0343 **
|
0.141
|
0.0098 NS
|
0.008
|
|
12
|
December
|
0.0217 NS
|
0.039
|
-9e-04 NS
|
0
|